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Markus Klein

Professor at University of Strathclyde

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United Kingdom

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Research Interests

Educational Psychology

100%

Special Education

50%

Education

100%

Student Achievement

50%

Sociology

30%

Regression Analysis

30%

Social Science

30%

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Recent Grants

Grant: Close

Is school absenteeism harmful to education and labour market outcomes?

Open Date: 2022-05-01

Close Date: 2024-04-01

Grant: Close

Bildungsexpansion, berufsstruktureller Wandel und Arbeitsmarkterträge tertiärer Bildung. Eine empirische Analyse der Berufschancen von Hochschulabsolventen im Zeitverlauf

Open Date: 2010-01-01

Close Date: 2012-12-01

Grant: Close

Social Inequalities in Educational Attainment: An Investigation into the Mediating Role of School Absenteeism

Open Date:

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Positions3

Publisher
source

Michael Vallely

University Name
.

University of Strathclyde

PhD Studentship: Do Educational Pathways Mitigate Social Class Inequalities in Early Labour Market Outcomes? Evidence from Growing Up in Scotland

[Fully-funded scholarship for 3 years covers all university tuition fees (at UK level) and an annual tax-free stipend. International students are eligible but must cover the difference between home and international fees unless exceptionally funded.] This fully-funded PhD studentship at the University of Strathclyde investigates whether educational pathways can mitigate social class inequalities in early labour market outcomes, using data from the Growing Up in Scotland study. The project is situated at the intersection of social mobility, educational inequality, and labour market stratification, with a specific focus on the Scottish context. The research aims to provide policy-relevant evidence on how education can promote social mobility and reduce labour market inequalities among young adults. The successful candidate will join a vibrant research environment and work under the supervision of Dr Michael Vallely, Professor Patricia Findlay, and Professor Markus Klein. The project will employ advanced quantitative methods, including regression analysis, and will require experience with longitudinal datasets and statistical software such as Stata or R. The findings are expected to contribute to the evidence base on educational inequality and inform policy debates in Scotland and beyond. The studentship is fully funded for three years, covering all university tuition fees at the UK level and providing an annual tax-free stipend at the UKRI rate. International students are welcome to apply; however, they must secure additional funding to cover the difference between home and international tuition fees unless they are exceptionally selected for full coverage. The position is open to candidates with a first-class or upper second-class Honours degree and a Masters degree in a social science discipline, with demonstrated competence in quantitative research methods. Experience with longitudinal data and statistical software is desirable. The application deadline is 30 April 2026, with a start date of 1 October 2026. Applicants should apply online via the University of Strathclyde portal and ensure they meet all eligibility criteria. Shortlisted candidates will be invited for interview. For further details, refer to the official advert or contact the supervisors directly.

2 months ago

Publisher
source

University of Strathclyde

University of Strathclyde

Fully Funded PhD in Educational Pathways, Social Mobility, and Labour Market Inequalities at University of Strathclyde

Fully funded PhD opportunity at the University of Strathclyde in the Strathclyde Business School / Department of Work, Employment and Organisation . The project is titled Do Educational Pathways Mitigate Social Class Inequalities in Early Labour Market Outcomes? Evidence from Growing Up in Scotland . It sits at the intersection of social mobility , social stratification , education , labour market transitions , and quantitative methods . The successful candidate will use data from Growing Up in Scotland to study how educational attainment and pathways shape early labour market outcomes and whether education reduces inequalities linked to social class background. Supervision is led by Dr Michael Vallely , with Professor Patricia Findlay and Professor Markus Klein as additional supervisors. This is a fully funded PhD studentship for 3 years, covering all university tuition fees at UK level plus an annual tax-free stipend. International applicants are welcome, but they must find additional funding for the difference between home and international tuition fees; exceptional international candidates may receive support for this gap. Eligibility highlights include a first-class or upper second-class Honours degree and a Masters degree in a social science-related discipline, plus demonstrated competence in applied quantitative methods such as regression analysis. Desirable experience includes longitudinal datasets and software such as Stata or R. If English is not your first language, an IELTS 6.5 (or equivalent) with no element below 5.5 is required. Applications open on 2026-03-12 and the deadline is 2026-04-30 . Applicants should apply online and upload the required documents only: covering letter, CV, two academic referees’ contact details, certified transcripts, and English language evidence if applicable. Remember to include the scholarship title in the Field of Study section.

2 months ago

Publisher
source

Michael Vallely

University Name
.

University of Strathclyde

PhD Studentship: Do Educational Pathways Mitigate Social Class Inequalities in Early Labour Market Outcomes? Evidence from Growing Up in Scotland

[Fully-funded scholarship for 3 years covers all university tuition fees (at UK level) and an annual tax-free stipend. International students are eligible but must fund the difference between home and international tuition fees unless exceptionally funded.] This fully-funded PhD studentship at the University of Strathclyde investigates whether educational pathways can mitigate social class inequalities in early labour market outcomes, using data from the Growing Up in Scotland study. The project is situated at the intersection of social mobility, educational inequality, and labour market stratification, aiming to provide policy-relevant evidence for Scotland and beyond. Supervised by Dr Michael Vallely, Prof Patricia Findlay, and Prof Markus Klein, the research will explore how educational attainment and pathways interact with social class origins to shape young adults' early career trajectories. The findings will contribute to the evidence base on educational inequality and social mobility, informing debates and policy on reducing labour market disparities. The studentship is funded for 36 months, covering all university tuition fees at the UK level and providing an annual tax-free stipend at the UKRI rate. International students are eligible to apply, but must secure funding for the difference between home and international tuition fees unless exceptionally supported. The project is open to full-time applicants only. Applicants must hold a first-class or upper second-class Honours degree (or equivalent) and a Masters degree in a social science related discipline. Essential skills include demonstrated competence in applied quantitative methods, particularly regression analysis, evidenced through coursework, dissertation, or research experience. A strong interest in social inequality, education, and labour market research is required. Experience with longitudinal datasets and familiarity with statistical software such as Stata or R are desirable. The application deadline is 30 April 2026, with a start date of 1 October 2026. Shortlisted candidates will be invited for interview. For further details and to apply, visit the University of Strathclyde's postgraduate research opportunities page. Contact supervisors for academic queries: Dr Michael Vallely ([email protected]), Prof Patricia Findlay ([email protected]), and Prof Markus Klein ([email protected]).

2 months ago

Articles16

Research Article on Advanced Machine Learning Applications

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2024

Research Article on Advanced Machine Learning Applications

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2024

Research Article on Advanced Machine Learning Applications

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2024

Research Article on Advanced Machine Learning Applications

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2024

Research Article on Advanced Machine Learning Applications

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2024

Research Article on Advanced Machine Learning Applications

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2024

Research Article on Advanced Machine Learning Applications

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2024

Research Article on Advanced Machine Learning Applications

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2024

Research Article on Advanced Machine Learning Applications

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2024

Research Article on Advanced Machine Learning Applications

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2024

Research Article on Advanced Machine Learning Applications

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2024

Research Article on Advanced Machine Learning Applications

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2024

Research Article on Advanced Machine Learning Applications

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2024

Research Article on Advanced Machine Learning Applications

Year:

2024

Collaborators7

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John Doe

Professor of Computer Science

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John Doe

Professor of Computer Science

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